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A Monocular Vision-Based Framework for Power Cable Cross-Section Measurement

Author

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  • Xiaoming Zhang

    (School of Geodesy and Geomatics, Wuhan University, No.129, Luoyu Road, Wuhan 430079, China
    Collaborative Innovation Center for Geospatial Technology, No.129, Luoyu Road, Wuhan 430079, China)

  • Hui Yin

    (School of Geodesy and Geomatics, Wuhan University, No.129, Luoyu Road, Wuhan 430079, China
    Collaborative Innovation Center for Geospatial Technology, No.129, Luoyu Road, Wuhan 430079, China)

Abstract

The measurements of the diameter of different layers, the thickness of different layers and the eccentricity of insulation layer in the cross-section of power cables are important items of power cable test, which currently depend on labor-intensive manual operations. To improve efficiency, automatic measurement methods are in urgent need. In this paper, a monocular vision-based framework for automatic measurement of the diameter, thickness, and eccentricity of interest in the cross-section of power cables is proposed. The proposed framework mainly consists of three steps. In the first step, the images of cable cross-section are captured and undistorted with the camera calibration parameters. In the second step, the contours of each layer are detected in the cable cross-section image. In order to detect the complete and accurate contours of each layer, the structural edges in the cross-section image are firstly detected and divided into individual layers, then unconnected edges are connected by arc-based method, and finally contours are refined by the proposed break detection and grouping (BDG) and linear trend-based correction (LTBC) algorithm. In the third step, the monocular vision-based cross-section dimension measurement is accomplished by placing a chessboard coplanar with the power cable cross-section plane. The homography matrix mapping pixel coordinates to chessboard world coordinates is estimated, and the diameter, thickness and eccentricity of specific layers are calculated by homography matrix-based measurement method. Simulated data and actual cable data are both used to validate the proposed method. The experimental results show that diameter, minimum thickness, mean thickness and insulation eccentricity of simulated image without additive noise are measured with root mean squared error (RMSE) of 0.424, 0.103 and 0.063 mm, and 0.002, respectively, those of simulated image with additive Gaussian noise and salt and pepper noise are measured with RMSE of 0.502, 0.243 and 0.058 mm and 0.001. Diameter, minimum thickness and mean thickness of actual cable images are measured with average RMSE of 0.768, 0.308 and 0.327 mm. The measurement error of insulation eccentricity of actual cable image is comparatively large, and the measurement accuracy should be improved.

Suggested Citation

  • Xiaoming Zhang & Hui Yin, 2019. "A Monocular Vision-Based Framework for Power Cable Cross-Section Measurement," Energies, MDPI, vol. 12(15), pages 1-26, August.
  • Handle: RePEc:gam:jeners:v:12:y:2019:i:15:p:3034-:d:255246
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    References listed on IDEAS

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